Reinforced Fuzzy Clustering-Based Ensemble Neural Networks

Kim, Eun-Hu; Oh, Sung‐Kwun; Pedrycz, Witold; Fu, Zunwei

doi:10.1109/tfuzz.2019.2911492

Cited by 25 publications

(10 citation statements)

References 42 publications

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“…Within the between cluster (Vb) variation, this variation is utilized to see the comes about of the change of information conveyance between clusters. The more prominent the Vb value, the way better the cluster (Gan, 2019) (Kim et al, 2020). To see the variations of all clusters, it can be seen at the V esteem, the littler the V value, the superior the cluster value.…”

Section: Ii3 Cluster Testingmentioning

confidence: 96%

Blackbox Testing Using Fuzzy Clustering Based on Boundary Value Analysis on The Text Opinion Mining Application in Traditional Culture Arts Presentation

Zubair

Sonalitha

Ratih

et al. 2020

Proceeding on International Conference of Science Management Art Research Technology

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The success of organizing a traditional work of art cannot be separated from the important role of data and information obtained from the public in general, and viewers or art connoisseurs in particular. This information is an indicator that can be used to measure the amount of public attention to traditional arts, which is an effort to promote traditional cultural arts. Data and information related to traditional artworks were obtained from filling out the instruments that were distributed to the public online to produce an opinion form that contained a complete description with a discussion containing the aesthetic of the artwork. Opinion data is needed as a measure of progress and preservation of a work of art. The linguistic measurement of opinion can be solved using fuzzy methods in a cryptic form that can be weighted. In this study, the authors tested the audience opinion text mining application on the presentation of traditional cultural artworks using fuzzy clustering using the functional testing method (Black box testing). Through this test will be discussed related to the menu or module to produce information.

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Section: Ii3 Cluster Testingmentioning

confidence: 96%

Blackbox Testing Using Fuzzy Clustering Based on Boundary Value Analysis on The Text Opinion Mining Application in Traditional Culture Arts Presentation

Zubair

Sonalitha

Ratih

et al. 2020

Proceeding on International Conference of Science Management Art Research Technology

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“…Another ensemble method decomposes the input space into Voronoi partitions (i.e., nonintersecting, convex partitions whose union is the input space) and associates a distinct sub-network for each partition. In [24], fuzzy C-means clustering is applied to partition the input space. In [25], a Boltzmann parameter has been used to reduce the degree of randomness of the genetic algorithm operators used in training.…”

Section: Deep Neural Network Ensemble Approachmentioning

confidence: 99%

“…The softmax output neuron functions as a switch, selecting the appropriate sub-network for input x i , which is hereafter referred as the 'winner' sub-network. The intermediate values of T have the effect of Voronoi partitioning X with 'fuzzy' boundaries as in [24]. At the end of each training epoch, the Boltzmann parameter is geometrically decreased by a factor γ ∈ (0, 1) (referred to as the 'cooling' rate) such that,…”

Section: Partitioning Using Unsupervised Learningmentioning

confidence: 99%

Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble

2021

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Outages in an overhead power distribution system are caused by multiple environmental factors, such as weather, trees, and animal activity. Since they form a major portion of the outages, the ability to accurately estimate these outages is a significant step towards enhancing the reliability of power distribution systems. Earlier research with statistical models, neural networks, and committee machines to estimate weather-related and animal-related outages has reported some success. In this paper, a deep neural network ensemble model for outage estimation is proposed. The entire input space is partitioned with a distinct neural network in the ensemble performing outage estimate in each partition. A novel algorithm is proposed to train the neural networks in the ensemble, while simultaneously partitioning the input space in a suitable manner. The proposed approach has been compared with the earlier approaches for outage estimation for four U.S. cities. The results suggest that the proposed method significantly improves the estimates of outages caused by wind and lightning in power distribution systems. A comparative analysis with a previously published model for animal-related outages further establishes the overall effectiveness of the deep neural network ensemble.

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“…Term Weighting aims to Identify the value or heft of a term based on the level of interest in the document. Period Frequency and Inverse Document Frequency (TF-IDF) is a weighting that is often used in information retrieval and text mining [19] [20]. TF is the frequency of the case of a term in the document.…”

Section: B Text Preprocessingmentioning

confidence: 99%

Combined Text Mining: Fuzzy Clustering for Opinion Mining on the Traditional Culture Arts Work

Sonalitha¹,

Zubair²,

Molyo³

et al. 2020

IJACSA

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The Indonesian government is currently intensifying work programs in the field of traditional arts and culture. In order to realize the promotion of the country's culture, the government has enacted a law on cultural promotion. One indicator of the achievement of the promotion of culture, among others, with the collection of data on traditional culture, the data mapping and data inventory can be processed into information and knowledge. In this research, indicators of performance indicators were compiled from connoisseurs of traditional works of art using data in the city of Malang, East Java, Indonesia. The results of the audience's opinion on cultural offerings can be used as a benchmark for the success of the promotion of traditional culture. When the culture is explored and tried to be displayed again, it is important to know the audience's satisfaction and understanding of the display that has just been witnessed. The results of the description of respondents in the form of opinions on the artwork will be collected as data processed using Text Mining with the Clustering of Fuzzy C-Means method to determine the audience's opinion about Feeling , which is related to feelings when viewing the beauty of the artwork, Value is related to the assessment to an art work that can be in the form of art weights contained in the work of art, and Emphasizing , which is related to empathy or respect for the art world, including professions related to the world such as dancers, musicians and others. The results achieved from this study show that has good performance on the proposed method. This can be known from the results of data testing using cluster variance V = 0.00000217901. Based on these values it can be concluded that the value of all cluster variants is good.

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Reinforced Fuzzy Clustering-Based Ensemble Neural Networks

Cited by 25 publications

References 42 publications

Blackbox Testing Using Fuzzy Clustering Based on Boundary Value Analysis on The Text Opinion Mining Application in Traditional Culture Arts Presentation

Blackbox Testing Using Fuzzy Clustering Based on Boundary Value Analysis on The Text Opinion Mining Application in Traditional Culture Arts Presentation

Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble

Combined Text Mining: Fuzzy Clustering for Opinion Mining on the Traditional Culture Arts Work

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